Robot Task Allocation based on Greedy-Face-Greedy Algorithm

Abstract

Two new algorithms (GFGF1 and GFGF2) for event finding in wireless sensor and robot networks based on the Greedy-Face-Greedy (GFG) routing are proposed in this paper. The purpose of finding the event (reported by sensors) is to allocate the task to the closest robot to act upon the event. Using two scenarios (event in or out of the network) and two topologies (random and random with hole) it is shown that GFGF1 always find the closest robot to the event but with more than twice higher communication cost compared to GFG, especially for the outside of the network scenario. GFGF2 features more than 4 times communication cost reduction compared to GFG but with percentage of finding the closest robot up to 90%.